Frank DiMaio
Impact in
- Structural Biology top 0.1%
- Advanced Electron Microscopy Techniques and Applications
- Molecular Biology top 0.2%
- Protein Structure and Dynamics
- RNA and protein synthesis mechanisms
Papers in
-
- Protein Structure and Dynamics 50
- RNA and protein synthesis mechanisms 40
- Glycosylation and Glycoproteins Research 7
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- Enzyme Structure and Function 53
- Co-authors
- David Baker (61 shared papers)Ray Yu‐Ruei Wang (8 shared papers)Yifan Song (6 shared papers)David E. Kim (8 shared papers)Hahnbeom Park (11 shared papers)Michael D. Tyka (5 shared papers)Yifan Cheng (4 shared papers)David Veesler (16 shared papers)
- Journals
- Proceedings of the National Academy of Sciences (13 papers)Science (11 papers)Nature Structural & Molecular Biology (10 papers)Structure (9 papers)Nature (9 papers)
- Partner nations
- United StatesUnited KingdomFrance
In The Last Decade
Frank DiMaio
147 papers receiving 13.9k citations
Frank DiMaio's Hit Papers
Peers
Comparison fields: 5 of 186
- Structural Biology 805
- Molecular Biology 9.6k
- Infectious Diseases 1.5k
- Endocrinology 370
- Cell Biology 998
Countries citing papers authored by Frank DiMaio
This map shows the geographic impact of Frank DiMaio's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Frank DiMaio with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Frank DiMaio more than expected).
Fields of papers citing papers by Frank DiMaio
This network shows the impact of papers produced by Frank DiMaio. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Frank DiMaio. The network helps show where Frank DiMaio may publish in the future.
Co-authors
The 25 scholars most cited alongside Frank DiMaio, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 150 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | The Rosetta All-Atom Energy Function for Macromolecular Modeling and Design Hit paper breakdown → | 2017 | 977 |
| 2 | High-Resolution Comparative Modeling with RosettaCM Hit paper breakdown → | 2013 | 824 |
| 3 | EMRinger: side chain–directed model and map validation for 3D cryo-electron microscopy Hit paper breakdown → | 2015 | 575 |
| 4 | Cryo-electron microscopy structure of a coronavirus spike glycoprotein trimer Hit paper breakdown → | 2016 | 390 |
| 5 | Structure prediction for CASP8 with all‐atom refinement using Rosetta Hit paper breakdown → | 2009 | 382 |
| 6 | Simultaneous Optimization of Biomolecular Energy Functions on Features from Small Molecules and Macromolecules Hit paper breakdown → | 2016 | 368 |
| 7 | De novo protein design by deep network hallucination Hit paper breakdown → | 2021 | 360 |
| 8 | Glycan shield and epitope masking of a coronavirus spike protein observed by cryo-electron microscopy Hit paper breakdown → | 2016 | 311 |
| 9 | 2016 | 307 | |
| 10 | Crystal structure of a monomeric retroviral protease solved by protein folding game players Hit paper breakdown → | 2011 | 303 |
| 11 | Relaxation of backbone bond geometry improves protein energy landscape modeling Hit paper breakdown → | 2013 | 294 |
| 12 | 2018 | 283 | |
| 13 | Alternate States of Proteins Revealed by Detailed Energy Landscape Mapping Hit paper breakdown → | 2010 | 280 |
| 14 | Atomic-accuracy models from 4.5-Å cryo-electron microscopy data with density-guided iterative local refinement Hit paper breakdown → | 2015 | 247 |
| 15 | De novo design of protein homo-oligomers with modular hydrogen-bond network–mediated specificity Hit paper breakdown → | 2016 | 236 |
| 16 | 2009 | 229 | |
| 17 | High thermodynamic stability of parametrically designed helical bundles Hit paper breakdown → | 2014 | 216 |
| 18 | Accurate prediction of protein–nucleic acid complexes using RoseTTAFoldNA Hit paper breakdown → | 2023 | 209 |
| 19 | Design of ordered two-dimensional arrays mediated by noncovalent protein-protein interfaces Hit paper breakdown → | 2015 | 195 |
| 20 | Structure of the Type VI Secretion System Contractile Sheath Hit paper breakdown → | 2015 | 190 |
About Frank DiMaio
Frank DiMaio is a scholar working on Molecular Biology, Materials Chemistry, Structural Biology, Genetics and Ecology, having authored 150 papers that have together received 14.0k indexed citations. Recurring topics across this work include Enzyme Structure and Function (53 papers), Protein Structure and Dynamics (50 papers), RNA and protein synthesis mechanisms (40 papers), Advanced Electron Microscopy Techniques and Applications (20 papers), Bacteriophages and microbial interactions (13 papers), Bacterial Genetics and Biotechnology (12 papers), Electron and X-Ray Spectroscopy Techniques (10 papers) and Glycosylation and Glycoproteins Research (7 papers). The work is most often cited by research in Structural Biology (805 citations), Molecular Biology (9.6k citations), Infectious Diseases (1.5k citations), Endocrinology (370 citations) and Cell Biology (998 citations). Frank DiMaio has collaborated with scholars based in United States, United Kingdom and France. Frequent co-authors include David Baker, Ray Yu‐Ruei Wang, Yifan Song, David E. Kim, Hahnbeom Park, Michael D. Tyka, Yifan Cheng, David Veesler, James Thompson and Edward H. Egelman. Their work appears in journals such as Proceedings of the National Academy of Sciences, Science, Nature Structural & Molecular Biology, Structure and Nature.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.